Different staple foods at lunch significantly reduced 120-min iAUC compared to glucose: noodles (β = −179.53, p<0.001) showed the greatest reduction, while meal timing had no significant effect on iAUC120 in outpatients with IGT or T2DM.
Observational (n=33)
No
Does meal timing and staple food type affect postprandial glycemic responses in outpatients with impaired glucose tolerance and type 2 diabetes mellitus?
Staple food types, but not meal timing, significantly affect postprandial glycemic responses in patients with dysglycemia, emphasizing the need for personalized nutrition.
Estimación del efecto: β = −59.49 (dinner vs breakfast) for iAUC120 (95% CI −114.68 to −4.30)
Tasa de eventos absoluta: 306% vs 366%
valor p: p=0.096 (adjusted) meal timing effect on iAUC120; overall time effect P=0.110 (not significant)
Objective: Effectively managing postprandial blood glucose is significant for impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM). We developed a streamlined and real-world framework and evaluated how meal timing and staple food type affect postprandial glycemic responses (PPGRs) and the influencing factors on inter-individual differences of PPGR. Materials and methods: We conducted a prospective observational study involving 33 patients with IGT and T2DM. Over a 1-week free-living period, participants completed 7 standardized meal tests: glucose solutions at breakfast, lunch, and dinner; steamed bread, rice, noodles, and oats at lunch. Linear mixed-effects models were used to compare PPGR differences of meal timing and staple food type effects. Linear regression models were applied to explore factors influencing inter-individual heterogeneity in PPGRs. Results: Participants deemed the framework simple and well tolerated. Meal timing had no significant effect on PPGR at 120 minutes (time effect P = 0.110) or 180 minutes (time effect P = 0.097). HOMA-IR was positively associated with the meal timing variability index (adjusted: β = 9.10, 95% CI: 3.01– 15.20, P = 0.005). Staple food types affected 120- and 180-minute incremental area under the curve (iAUC), relative peak glucose, and glucose fluctuation amplitude (staple food type effect P 0.05). Those born in northern China had a significantly higher refined staple food sensitivity index (adjusted: β = 267.14, 95% CI: 59.18– 475.09, P = 0.014). Conclusion: The framework enables convenient, outpatient-based assessment of PPGRs and is highly acceptable to patients. We need to focus not only on the group-level general characteristics of PPGRs but also analyze their individual-level heterogeneity; this emphasizes the critical role of personalized nutrition. Keywords: continuous glucose monitoring, framework, meal timing, postprandial glycemic response, staple food type, type 2 diabetes mellitus
Wang et al. (Sun,) conducted a observational in Outpatients aged 18-75 years with impaired glucose tolerance (IGT) or type 2 diabetes mellitus (T2DM), HbA1c <11%, BMI 18-35 kg/m2, untreated or on stable medication for >3 months (n=33). Standardized meals with 50g carbohydrates: glucose beverage at breakfast, lunch, dinner; steamed bread, rice, noodles, oats at lunch vs. Same meal at different times (glucose) or different staples at lunch (glucose beverage as reference) was evaluated on Incremental area under the curve at 120 minutes postprandial glucose (iAUC120) measured by continuous glucose monitoring (β = −59.49 (dinner vs breakfast) for iAUC120, 95% CI −114.68 to −4.30, p=0.096 (adjusted) meal timing effect on iAUC120; overall time effect P=0.110 (not significant)). Different staple foods at lunch significantly reduced 120-min iAUC compared to glucose: noodles (β = −179.53, p<0.001) showed the greatest reduction, while meal timing had no significant effect on iAUC120 in outpatients with IGT or T2DM.